Analyzing the color availability of AI-generated posters based on K-means clustering: 74% orange, 38% cyan, 32% yellow, and 28% blue-cyan

Abstract

In this exploratory study, we delved deeply into the intricate interplay of color choices within AI-generated and human-designed posters, analyzing a sample of 120 instances from each category. While it is suggested that human designers may integrate cultural, emotional, and situational contexts into their creations, AI models largely base their selections on vast datasets and pattern recognition. Although AI exhibited prowess in replicating established design parameters, the study underlined the importance of critically assessing its outputs. The quantitative analysis illuminated overarching similarities in primary color selections. However, the AI's diversity in color remains less concentrated than that of human, suggesting a gap in the AI's capacity to match human expertise in color proportioning and distribution. As AI continues to evolve, it is crucial to discern its capabilities and potential limitations in the design domain, ensuring it augments human creativity rather than supplanting it. Notably, the research refrains from seeking human validation, aiming instead for an objective, data-driven reflection on the convergences and divergences between AI-generated and human designs.